Triple

T8237256
Position Surface form Disambiguated ID Type / Status
Subject Romblon E192440 entity
Predicate hasMunicipality P847 FINISHED
Object San Jose
San Jose is a coastal municipality in the Philippine province of Romblon known for its island landscapes and fishing communities.
 E796976 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: San Jose | Statement: [Romblon, hasMunicipality, San Jose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San Jose
Context triple: [Romblon, hasMunicipality, San Jose]
  • A. San Jose
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • B. San Jose
    San Jose is the main town on the island of Tinian in the Northern Mariana Islands, serving as its administrative and population center.
  • C. San Jose
    San Jose is a coastal municipality in the Philippine province of Negros Oriental known for its rural communities and proximity to Dumaguete City.
  • D. San Jose
    San Jose is a coastal municipality in the province of Northern Samar in the Eastern Visayas region of the Philippines.
  • E. San Jose
    San Jose is a municipality in the province of Tarlac in the Central Luzon region of the Philippines, known for its predominantly agricultural economy.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: San Jose
Triple: [Romblon, hasMunicipality, San Jose]
Generated description
San Jose is a coastal municipality in the Philippine province of Romblon known for its island landscapes and fishing communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: San Jose
Target entity description: San Jose is a coastal municipality in the Philippine province of Romblon known for its island landscapes and fishing communities.
  • A. San Jose
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • B. San Jose
    San Jose is the main town on the island of Tinian in the Northern Mariana Islands, serving as its administrative and population center.
  • C. San Jose
    San Jose is a coastal municipality in the Philippine province of Negros Oriental known for its rural communities and proximity to Dumaguete City.
  • D. San Jose
    San Jose is a coastal municipality in the province of Northern Samar in the Eastern Visayas region of the Philippines.
  • E. San Jose
    San Jose is a municipality in the province of Tarlac in the Central Luzon region of the Philippines, known for its predominantly agricultural economy.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca82dc8f148190a2c75a98501a7b91 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb783929c081909db1182947755bae completed March 31, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1076c28b08190a5a0ab74ccfb9909 completed April 4, 2026, 12:43 p.m.
NEDg Description generation batch_69d107ebdd4c819084eff70c0b31d693 completed April 4, 2026, 12:45 p.m.
NED2 Entity disambiguation (via description) batch_69d1085b8ce4819086fe3a006f9ea13f completed April 4, 2026, 12:47 p.m.
Created at: March 30, 2026, 5:47 p.m.